Clinical and biological relevance of the transcriptomic-based prostate cancer metastasis subtypes MetA-C
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ABSTRACT:
PROVIDER: PRJNA782617 | ENA |
REPOSITORIES: ENA
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Project description:Transcriptomic profiling of metastasis tissue samples obtained from prostate cancer patients was performed using Clariom D human arrays.
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Project description:To evaluate the prognostic relevance of molecular subtypes and key transcription factors in pancreatic ductal adenocarcinoma (PDAC), we performed gene expression analysis of whole-tumor tissue obtained from 118 surgically resected PDAC and 13 control samples.
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Project description:Head and neck squamous cell carcinoma (HNSCC) is a disease with heterogeneous clinical behavior and response to therapies. Despite the introduction of multimodality treatment, 40-50% of patients with advanced disease recur. Therefore, there is an urgent need to improve the classification beyond the current parameters in clinical use to better stratify patients and the therapeutic approaches. Following a meta-analysis approach we built a large training set to whom we applied a Disease-Specific Genomic Analysis (DSGA) to identify the disease component embedded into the tumor data. Eleven independent microarray datasets were used as validation sets. Six different HNSCC subtypes that summarize the aberrant alterations occurring during tumor progression were identified. Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal. Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes. The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes. To conclude, we report a robust molecularly defined subtype classification in HNSCC that can improve patient selection and pave the way to the development of appropriate therapeutic strategies.
| S-EPMC4496244 | biostudies-literature
Project description:From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies.
2013-05-22 | GSE40966 | GEO
Project description:Purpose: The biological subtypes of breast cancer designated as Luminal A, Luminal B, HER2+/ER-, and Basal-like are clinically important for prognosis and planning treatment strategies. Recognizing that there is a continuum in both the spectrum of breast cancer disease and the risk of survival, we sought to develop a clinical test for the biological subtypes using a supervised risk classier.Methods: Microarray and real-time quantitative RT-PCR (qRT-PCR) data from 189 samples, procured as fresh-frozen and formalin-fixed, paraffin-embedded tissues, were used to statistically select prototypical samples and genes for the biological subtypes of breast cancer. Predictions for biological subtype and risk of recurrence were determined for different stages of disease, treatments, and across analytical platforms. Results: The biological subtype predictions on a large combined microarray test set showed prognostic significance across all patients (1244 subjects; p<0.0001), on node negative patients with no adjuvant systemic therapy (738 subjects; p<0.0001), and on patients treated with endocrine therapy (404 subjects; p=0.001). Analysis of a neoadjuvant chemotherapy study revealed a high pathologic complete response (pCR) rate in HER2+/ER- and Basal-like patients. The subtype and risk predications were also highly significant when using the qRT-PCR assay from archived FFPE breast cancers. Conclusion: Our risk predictor based on distance to biological subtype centroids provides a continuous risk score that applies to all stages of breast cancer given current therapies. The assay can be performed using archived breast tissues and a real-time qRT-PCR assay, thus facilitating application to retrospective cohorts and clinical samples. Keywords: reference x sample
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Project description:From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and 19 non-tumoral colorectal mucosas, and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies.
2013-05-22 | GSE39582 | GEO
Project description:During development, the human brain orchestrates the generation of hundreds of diverse cell types, and recent transcriptomic atlases of the developing human cortex provide new opportunities to identify novel regulators of cell fate specification. We have conducted an integrated meta-analysis of seven recently published single-cell transcriptomic profiles of the developing human cortex, generating a meta-atlas of 225 meta-modules. By tracking the activity of these meta-modules throughout development and comparing this to datasets from the adult human as well as the developing and adult mouse, we identified modules with potential roles in the transition from neurogenesis to gliogenesis and neuronal subtype maturation. The cell type and developmental state at which these modules exist was validated in primary samples from the developing human brain. Of particular interest, we identified and validated a module associated with both developing human deep layer neurons and human adult deep layer neuronal subtypes expressing the terminal differentiation marker FEZF2. Though FEZF2 is neither a member of nor co-expressed with our deep layer-associated gene module, almost half of module genes are putative FEZF2 targets, including TSHZ3, a transcription factor associated with neurodevelopmental disorders such as autism. Knockdown experiments in human cortical organoid models confirm that both FEZF2 and TSHZ3 are necessary for deep layer neuron specification. Importantly, we observe that subtle manipulations of these transcription factors result in slight changes in module activity, but together yield strong differences in cell fate. Our analyses therefore reveal a gene network that required to generate deep layer neuronal subtypes, demonstrating the ability of our meta-atlas to engender further mechanistic analyses of cortical fate specification. We anticipate this resource being useful for the study of co-expression programs across diverse biological questions related to the developing neocortex.
2023-09-12 | GSE242779 | GEO